Catching the recent trend of data is an important issue when mining frequent itemsets from data streams. To prevent from storing the whole transaction data within the sliding windo...
In this paper, we investigate a new approach to process queries in data stream applications. We show that reference locality characteristics of data streams could be exploited in ...
Feifei Li, Ching Chang, George Kollios, Azer Besta...
Equi-depth histograms represent a fundamental synopsis widely used in both database and data stream applications, as they provide the cornerstone of many techniques such as query ...
We present algorithms for fast quantile and frequency estimation in large data streams using graphics processor units (GPUs). We exploit the high computational power and memory ba...
Naga K. Govindaraju, Nikunj Raghuvanshi, Dinesh Ma...
Performing data mining tasks in streaming data is considered a challenging research direction, due to the continuous data evolution. In this work, we focus on the problem of clust...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...